Plotly and flexdashboard

Some examples of plotly plots

library(tidyverse)

## -- Attaching packages ----------------------------------------------------------------------------- tidyverse 1.2.1 --

## √ ggplot2 3.0.0     √ purrr   0.2.5
## √ tibble  1.4.2     √ dplyr   0.7.6
## √ tidyr   0.8.1     √ stringr 1.3.1
## √ readr   1.1.1     √ forcats 0.3.0

## -- Conflicts -------------------------------------------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(viridis)

## Loading required package: viridisLite

library(p8105.datasets)

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
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##     layout

set.seed(1)

data(nyc_airbnb)
nyc_airbnb = 
  nyc_airbnb %>% 
  mutate(rating = review_scores_location / 2) %>%
  select(boro = neighbourhood_group, neighbourhood, rating, price, room_type,
         latitude, longitude) %>%
  filter(!is.na(rating), 
         boro == "Manhattan",
         room_type == "Entire home/apt",
         price %in% 100:500)  %>% 
  sample_n(5000)

Plotly scatterplot

Create plotly scatterplot. Scatter plots have different modes. Used mutate to create a new variable called text_label. indicates new line for rating. Mapping text_lable to text.

nyc_airbnb %>%
  mutate(text_label = str_c("Price: $", price, '\nRating: ', rating)) %>% 
  plot_ly(x = ~longitude, y = ~latitude, type = "scatter", mode = "markers",
          alpha = 0.5, 
          color = ~price,
          text = ~text_label)

Plotly Boxplot

common_neighborhoods =
  nyc_airbnb %>% 
  count(neighbourhood, sort = TRUE) %>% 
  top_n(8) %>% 
  select(neighbourhood)

## Selecting by n

inner_join(nyc_airbnb, common_neighborhoods,
             by = "neighbourhood") %>% 
  mutate(neighbourhood = fct_reorder(neighbourhood, price)) %>% 
  plot_ly(y = ~price, color = ~neighbourhood, type = "box",
          colors = "Set2")

Plotly barchart

nyc_airbnb %>% 
  count(neighbourhood) %>% 
  mutate(neighbourhood = fct_reorder(neighbourhood, n)) %>% 
  plot_ly(x = ~neighbourhood, y = ~n, color = ~neighbourhood, type = "bar")

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

## Warning in RColorBrewer::brewer.pal(N, "Set2"): n too large, allowed maximum for palette Set2 is 8
## Returning the palette you asked for with that many colors

ggplotly

The code below recreates our scatterplot using ggplot. We then used ggplotly, converting a ggplot object straight to an interactive graphic.

scatter_ggplot = 
  nyc_airbnb %>%
  ggplot(aes(x = longitude, y = latitude, color = price)) +
  geom_point(alpha = 0.25) +
  scale_color_viridis() +
  coord_cartesian() +
  theme_classic()

ggplotly(scatter_ggplot)

boxplot can be created in a similiar way

box_ggplot = 
  inner_join(nyc_airbnb, common_neighborhoods,
             by = "neighbourhood") %>% 
  mutate(neighbourhood = fct_reorder(neighbourhood, price)) %>% 
  ggplot(aes(x = neighbourhood, y = price, fill = neighbourhood)) +
  geom_boxplot() +
  theme_classic() + 
  theme(axis.text.x = element_text(angle = 90, hjust = 1))

ggplotly(box_ggplot)

Flexdashboard